How to calculate multiobjective optimization cost for ordinary problems?
I eventually used the keep-efficient function from this answer to calculate the Pareto front and used the k-means function to calculate the centroid of the front. This gave me the approximate knee-point of the front, which is usually the optimal solution. One of the calculations was to maximise the distance moved in x direction (dx) vs. minimising the energy consumed (e), so since the x axis needed positive maximization and the y axis needed minimization, I inverted the y axis, since min(f(y)) = - max(-f(y)). This helped get the pareto front toward the top right side of the graph and both the x and y axes were maximization objectives. The optimal point calculated was the robot that had the best fitness.